Fig 1.
Evasion at different levels of the cancer-immunity cycle in each cluster.
Fig 2.
The clustering results for the sequential biclustering.
(A) The heatmap representing the level of gene expression (rows) in different clusters of patients (columns). (B) The percentage of different breast cancer receptor subtype and (C) lobular and ductal carcinomas, ILC and IDC, per cluster.
Table 1.
The association of clusters with breast cancer subtypes (receptor status).
Table 2.
The association of clusters with invasive lobular and ductal carcinoma subgroups, ILC and IDC, respectively.
Fig 3.
Pathway analysis based on the log2 fold change for clusters 1 and 4 compared to normal.
Fold change level of molecules involved in antigen processing and presentation molecules in cluster 1 (A) and cluster 4 (B). Fold change level of molecules involved in leukocyte recruitment in cluster 1 (C) and cluster 4 (D). These results show how cluster 1 genes for the first 2 steps of the cancer-immunity cycle are up-regulated while those of cluster 4 are mostly downregulated. These pathways and others for other clusters and steps of the cancer-immunity pathway are in S5 File. The color scale ranges from the downregulated expression in green (-1 fold), to the non-differential expression in grey, to the up-regulated expression in red (+1 fold).
Fig 4.
Classification tree with 12 biomarkers and their log2 gene expression cutoffs for the identified clusters (CL).
Interleukin-2 receptor subunit gamma (IL2RG), ATP-binding cassette sub-family B member 1 (ABCB1), cluster of differentiation-40 ligand (CD40LG), decorin (DCN), lymphocyte-specific protein tyrosine kinase (LCK), selectin-P (SELP), estrogen receptor-1 (ESR1), glucose-6-phosphate dehydrogenase (G6PD), programmed cell death-1 (PDCD1), cluster of differentiation-3 subunit gamma.
Table 3.
The rationale for deciding the immune evasion mechanisms (M).
Table 4.
The mechanism of evasion in each cluster and the potential immunotherapies for future clinical trials.